Latent sub-structural resilience mechanisms in temporal human mobility networks during urban flooding

Abstract

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities.

Deep Learning-driven Community Resilience Rating based on Intertwined Socio-Technical Systems Features

“…The area of land use type 71 (grassland/herbaceous) in each grid cell is calculated as its green space area. 𝐺𝑆_𝐵𝐶 𝑖 = ∑ 𝐺_𝐵𝐶 𝑗 𝑗 𝑓𝑜𝑟 𝑗 𝑖𝑛 𝐺𝑆 𝑗 (9) where, 𝐺𝑆_𝐵𝐶 𝑖 is the green space area of grid cell 𝑖, 𝐺_𝐵𝐶 𝑗 is the intersected area of NLCD pixel in type 71 cell 𝑗 with grid cell 𝑖, and 𝐺𝑆 𝑗 is the set of NLCD pixels intersected with grid cell 𝑖. Road density is used to measure the resourcefulness of the transportation system.…”

“…Also, previous research on community resilience focused mostly on a particular subsystem. Frequently studied are transportation systems [7][8][9][10] , power systems 11,12 , communication systems 13 , and social systems 14 . While these studies provide insights about the resilience of individual systems, they fail to provide comprehensive resilience ratings across different areas of a community.…”

Informing Urban Flood Risk Adaptation by Integrating Human Mobility Big Data During Heavy Precipitation

“…However, very few of them take a step further to estimate how human mobility leads to highly heterogeneous population distribution and, consequently, results in dynamic urban flood risk exposure. Another major gap in the literature is that these studies mostly focus on a single city or a few case cities, which makes it hard to explain variations across cities and recommend practical and effective adaptive interventions for other regions. , …”

“…Another major gap in the literature is that these studies mostly focus on a single city or a few case cities, which makes it hard to explain variations across cities and recommend practical and effective adaptive interventions for other regions. 33,34 To close the research gaps in urban flood risk mapping and inform adaptation at finer scales, this study developed a novel detrending framework and pictured rainfall-induced mobility perturbation at a high spatial resolution (500 m grid cell), leveraging a data set of ∼2.6 million mobile phone records obtained during 2018 summer in Jiangsu Province, China. Emerging hot−cold spots of mobility variation were identified, revealing the shocks in citizens' daily routines facing heavy precipitation events.…”

Enhancing Road Safety Decision-Making through Analysis of Youth Survey Data: A Descriptive Statistical Approach

“…This significance is particularly evident among the young, underscoring their critical role in promoting societal progress [4]. However, scientific data suggest that mobility has significant negative consequences as well [5][6][7]. Every year, an estimated 400,000 people aged 15 to 29 die in road traffic incidents worldwide, highlighting the adverse impact of mobility on this demographic [8].…”